Pain
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Randomized Controlled Trial
Conflicts hurt: social stress predicts elevated pain and sadness after mild inflammatory increases.
Individuals respond differently to inflammation. Pain, sadness, and fatigue are common correlates of inflammation among breast cancer survivors. Stress may predict response intensity. ⋯ At each visit, a trained experimenter administered the Daily Inventory of Stressful Events to assess social and nonsocial stress exposure within the past 24 hours. After statistical adjustment for relevant demographic and behavioral covariates, the most consistent results were that survivors who reported more chronic social stress reported more pain and sadness in response to IL-1Ra increases. Frequent and ongoing social stress may sensitize the nervous system to the effects of inflammation, with potential implications for chronic pain and depression risk among breast cancer survivors.
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Chronic pain (CP) is often accompanied by mental disorders (MDs). However, little is known concerning the long-term effect of MDs, personality traits, and early-life traumatic events (ETEs) on CP course. Accordingly, we aimed to prospectively assess the associations of major depressive disorders (MDDs), anxiety disorders, personality traits, and ETEs with the incidence and the persistence of CP in middle-aged and older community dwellers. ⋯ Our results suggest that personality traits are associated with both CP occurrence and persistence, whereas the MDDs may be more associated with CP persistence. Both personality and MDD are accessible to psychotherapy, and MDD is also accessible to pharmacotherapy. Hence, these therapeutic measures might decrease the risk of CP and its persistence.
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Shoulder disorders are common and associated with high societal costs, especially for a small group of patients. Prognostic factors can help identify high-cost patients, which is crucial to optimize early identification and develop tailored interventions. We aimed to identify prognostic factors for high societal costs, to examine whether the prognostic factors were similar for high healthcare costs and high costs of sick leave, and to investigate the model's robustness across 4 diagnostic categories. ⋯ Prognostic factors for high healthcare costs were high age, comorbidity, and hospital admission the year before diagnosis. The model was robust across diagnostic categories and sensitivity analyses. In the validation sample, the primary model's discriminative ability was good (AUC = 0.80) and the model explained 28% of the variation in the outcome (Nagelkerke R2 ).
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Although preclinical studies generally report robust antinociceptive effects of cannabinoids in rodent persistent pain models, randomized controlled trials in chronic pain patients report limited pain relief from cannabis/cannabinoids. Differences between animal and human studies that may contribute to these discrepant findings include route of cannabis/cannabinoid administration, type of cannabis/cannabinoid, and how pain is measured. To address these factors, rats with complete Freund adjuvant (CFA)-induced hind paw inflammation were exposed acutely or repeatedly to vaporized cannabis extract that was either tetrahydrocannabinol (THC) or cannabidiol (CBD)dominant. ⋯ Acute exposure to vaporized CBD-dominant cannabis extract (200 mg/mL) did not produce any effects in either sex; repeated exposure to this extract (100, 200, or 400 mg/mL) decreased mechanical allodynia in male rats only. Sex differences (or lack thereof) in the effects of vaporized cannabis extracts were not explained by sex differences in plasma levels of THC, CBD, or their major metabolites. These results suggest that although vaporized THC-dominant extract is likely to be modestly effective against inflammatory pain in both male and female rats, tolerance may develop, and the CBD-dominant extract may be effective only in male rats.
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Current automated pain assessment methods only focus on infants or youth. They are less practical because the children who suffer from postoperative pain in clinical scenarios are in a wider range of ages. In this article, we present a large-scale Clinical Pain Expression of Children (CPEC) dataset for postoperative pain assessment in children. ⋯ The CPANN achieves 82.1% accuracy and 73.9% macro-F1 score on the testing set of CPEC. The CPANN is faster, more convenient, and more objective compared with using pain scales according to the specific type of pain or children's condition. This study demonstrates the effectiveness of deep learning-based method for automated pain assessment in children.